On the Matrix Inversion Approximation Based on Neumann Series in Massive MIMO Systems

Zero-Forcing (ZF) has been considered as one of the potential practical precoding and detection method for massive MIMO systems. One of the most important advantages of massive MIMO is the capability of supporting a large number of users in the same time-frequency resource, which requires much larger dimensions of matrix inversion for ZF than conventional multi-user MIMO systems. In this case, Neumann Series (NS) has been considered for the Matrix Inversion Approximation (MIA), because of its suitability for massive MIMO systems and its advantages in hardware implementation. The performance-complexity trade-off and the hardware implementation of NS-based MIA in massive MIMO systems have been discussed. In this paper, we analyze the effects of the ratio of the number of massive MIMO antennas to the number of users on the performance of NS-based MIA. In addition, we derive the approximation error estimation formulas for different practical numbers of terms of NS-based MIA. These results could offer useful guidelines for practical massive MIMO systems.Comment: accepted to conference; Proc. IEEE ICC 201

Approximative Matrix Inverse Computations for Very-large MIMO and Applications to Linear Pre-coding Systems

In very-large multiple-input multiple-output (MIMO) systems, the BS (base station) is equipped with very large number of antennas as compared to previously considered systems. There are various advantages of increasing the number of antennas, and some schemes would require handling large matrices for joint processing (pre-coding) at the base station. The dirty paper coding (DPC) is an optimal pre-coding scheme and has a very high complexity. However with increasing number of BS antennas linear pre-coding performance tends to that of the optimal DPC. Although linear pre-coding is less complex than DPC, there is a need to compute pseudo inverses of large matrices. In this paper we present a low complexity approximation of down-link Zero Forcing linear pre-coding for very-large multi-user MIMO systems. Approximation using a Neumann series expansion is opted for inversion of matrices over traditional exact computations, by making use of special properties of the matrices, thereby reducing the cost of hardware. With this approximation of linear pre-coding, we can significantly reduce the computational complexity for large enough systems, i.e., where we have enough BS antenna elements. For the investigated case of 8 users, we obtain 90% of the full ZF sum rate, with lower computational complexity, when the number of BS antennas per user is about 20 or more

Exploiting the increasing correlation of space constrained massive MIMO for CSI relaxation

In this paper, we explore low-complexity transmission in physically-constrained massive multiple-input multiple-output (MIMO) systems by means of channel state information (CSI) relaxation. In particular, we propose a strategy to take advantage of the correlation experienced by the channels of neighbour antennas when deployed in tightly packed antenna arrays. The proposed scheme is based on collecting CSI for only a subset of antennas during the pilot training stage and, subsequently, using averages of the acquired CSI for the remaining closely-spaced antennas. By doing this, the total number of radio frequency (RF) chains, for both CSI acquisition and data transmission, and the baseband signal processing are reduced, hence simplifying the overall system operation. At the same time, this impacts the quality of the channel estimation produced after the CSI acquisition process. To characterize this tradeoff, we explore the impact that the number of antennas with instantaneous CSI has on the performance, signal processing complexity, and energy efficiency of time-division duplex (TDD) systems. The analytical and simulation results presented in this paper show that the application of the proposed strategy in size-constrained antenna arrays is able to significantly enhance the energy efficiency against systems with full CSI availability, while approximately preserving their average performance

Modeling the near-field of extremely large aperture arrays in massive MIMO systems

Massive multiple-input multiple-output (MIMO) is a key technology in modern cellular wireless communication systems to attain a very high system throughput in a dynamic multi-user environment. Massive MIMO relies on deploying base stations equipped with a large number of antenna elements. One possible way to deploy base stations equipped with hundreds or thousands of antennas is creating extremely large aperture arrays. In this paper, we investigate channel modeling aspects of massive MIMO systems with large aperture arrays, in which many users are located in the near-field of the aperture. Oneand two-dimensional antenna geometries, different propagation models, and antenna element patterns are compared in terms of inter-user correlation, condition number of the multi-user channel matrix, and spectral efficiency to identify key design parameters and essential modeling assumptions. As our analysis reveals by choosing spectral-efficiency as a design objective, the size of the aperture is the critical design parameter

대규모 다중 안테나 환경에서 낮은 복잡도의 다중 사용자 신호전송에 관한 연구

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·컴퓨터공학부, 2020. 8. 이용환.Advanced wireless communication systems may employ massive multi-input multi-output (m-MIMO) techniques for performance improvement. A base station equipped with an m-MIMO configuration can serve a large number of users by means of beamforming. The m-MIMO channel becomes asymptotically orthogonal to each other as the number of antennas increases to infinity. In this case, we may optimally transmit signal by means of maximum ratio transmission (MRT) with affordable implementation complexity. However, the MRT may suffer from inter-user interference in practical m-MIMO environments mainly due to the presence of insufficient channel orthogonality. The use of zero-forcing beamforming can be a practical choice in m-MIMO environments since it can easily null out inter-user interference. However, it may require huge computational complexity for the generation of beam weight. Moreover, it may suffer from performance loss associated with the interference nulling, referred to transmission performance loss (TPL). The TPL may become serious when the number of users increases or the channel correlation increases in spatial domain. In this dissertation, we consider complexity-reduced multi-user signal transmission in m-MIMO environments. We determine the beam weight to maximize the signal-to-leakage plus noise ratio (SLNR) instead of signal-to-interference plus noise ratio (SINR). We determine the beam direction assuming combined use of MRT and partial ZF that partially nulls out interference. For further reduction of computational complexity, we determine the beam weight based on the approximated SLNR. We consider complexity-reduced ZF beamforming that generates the beam weight in a group-wise manner. We partition users into a number of groups so that users in each group experience low TPL. We approximately estimate the TPL for further reduction of computational complexity. Finally, we determine the beam weight for each user group based on the approximated TPL.차세대 무선 통신 시스템에서 성능 향상을 위해 대규모 다중 안테나 (massive MIMO) 기술들을 사용할 수 있다. 대규모 안테나를 가진 기지국은 많은 수의 사용자들을 빔포밍 (beamforming)으로 서비스해줄 수 있다. 안테나 수가 무한히 증가함에 따라서 채널은 점근적으로 서로 직교 (orthogonal)하게 된다. 이러한 경우, 낮은 실장 복잡도를 가지는 최대 비 전송 (maximum ratio transmission)을 사용함으로써 신호전송을 최적화할 수 있다. 하지만, 현실적인 대규모 다중 안테나 환경에서는 채널 직교성이 충분하지 못하기 때문에 최대 비 전송은 간섭에 의한 성능 저하를 겪을 수 있다. 제로-포싱 (zero-forcing) 빔포밍은 간섭을 쉽게 제거할 수 있기 때문에 대규모 다중 안테나 환경에서 현실적인 선택이 될 수 있다. 하지만, 제로-포싱은 빔 가중치 (beam weight) 생성으로 인해 높은 계산 복잡도를 요구할 수 있다. 뿐만 아니라, 제로-포싱은 간섭 제거에 대한 대가로 심각한 성능 저하 (즉, transmission performance loss; TPL)를 겪을 수 있다. TPL은 사용자 수가 많거나 채널의 공간 상관도가 클 때 더 심각해질 수 있다. 본 논문에서 대규모 다중 안테나 환경에서 낮은 복잡도의 다중 사용자 신호전송을 고려한다. 제안 기법은 신호-대-간섭 및 잡음 비 (signal-to-interference plus noise ratio) 대신 신호-대-유출 및 잡음 비 (signal-to-leakage plus noise ratio)를 최대화하는 빔 가중치를 결정한다. 제안 기법은 최대 비 전송과 간섭을 선택적으로 제거하는 부분 제로-포싱 (partial zero-forcing)의 사용을 기반으로 빔 방향을 결정한다. 계산 복잡도를 더 감소시키기 위해서, 제안 기법은 근사화된 신호-대-유출 및 잡음비를 사용하여 빔 가중치를 결정한다. 본 논문에서 그룹 기반으로 빔 가중치를 생성하는 낮은 복잡도의 제로-포싱 빔포밍 전송을 고려한다. 제안 기법은 사용자들이 낮은 TPL을 갖도록 사용자들을 다수의 그룹으로 분리시킨다. 계산 복잡도를 더 감소시키기 위해서, 제안 기법은 TPL을 근사적으로 추정한다. 마지막으로, 제안 기법은 근사화된 TPL을 기반으로 형성된 각 사용자 그룹에 대하여 빔 가중치를 결정한다.Chapter 1. Introduction 1 Chapter 2. System model 10 Chapter 3. Complexity-reduced multi-user signal transmission 15 3.1. Previous works 15 3.2. Proposed scheme 24 3.3. Performance evaluation 47 Chapter 4. User grouping-based ZF transmission 57 4.1. Spatially correlated channel 57 4.2. Previous works 59 4.3. Proposed scheme 66 4.4. Performance evaluation 87 Chapter 5. Conclusions and further research issues 94 Appendix 97 A. Proof of Lemma 3-4 97 B. Proof of Lemma 3-5 100 C. Proof of strict quasi-concavity of SLNR_(k) 101 References 103 Korean Abstract 115Docto

Energy-Efficient System Design for Future Wireless Communications

The exponential growth of wireless data traffic has caused a significant increase in the power consumption of wireless communications systems due to the higher complexity of the transceiver structures required to establish the communication links. For this reason, in this Thesis we propose and characterize technologies for improving the energy efficiency of multiple-antenna wireless communications. This Thesis firstly focuses on energy-efficient transmission schemes and commences by introducing a scheme for alleviating the power loss experienced by the Tomlinson-Harashima precoder, by aligning the interference of a number of users with the symbols to transmit. Subsequently, a strategy for improving the performance of space shift keying transmission via symbol pre-scaling is presented. This scheme re-formulates complex optimization problems via semidefinite relaxation to yield problem formulations that can be efficiently solved. In a similar line, this Thesis designs a signal detection scheme based on compressive sensing to improve the energy efficiency of spatial modulation systems in multiple access channels. The proposed technique relies on exploiting the particular structure and sparsity that spatial modulation systems inherently possess to enhance performance. This Thesis also presents research carried out with the aim of reducing the hardware complexity and associated power consumption of large scale multiple-antenna base stations. In this context, the employment of incomplete channel state information is proposed to achieve the above-mentioned objective in correlated communication channels. The candidate’s work developed in Bell Labs is also presented, where the feasibility of simplified hardware architectures for massive antenna systems is assessed with real channel measurements. Moreover, a strategy for reducing the hardware complexity of antenna selection schemes by simplifying the design of the switching procedure is also analyzed. Overall, extensive theoretical and simulation results support the improved energy efficiency and complexity of the proposed schemes, towards green wireless communications systems